Summary

1. In general, conservation seeks to prevent further habitat loss but in many cases there is a need to reverse habitat degradation. Restoration of habitat is necessary to achieve biodiversity conservation goals but often it is a costly and time-intensive process. Prioritization of where and when habitat is restored can help to ensure the cost-effective delivery of desired outcomes.

2. We develop a restoration prioritization decision support tool to identify the combination of restoration sites and the schedule for their implementation most likely to deliver the greatest utility for a fixed budget and operational constraints. We use a case study to apply our prioritization approach in order to illustrate the data that can be employed to parameterise the analysis and the outputs that are able to inform restoration planning. We compare restoration schedules under alternative utility functions to demonstrate trade-offs associated with different objectives, assumptions and preferences for particular outcomes.

3. Our prioritization approach is spatially and temporally explicit and accounts for the costs and benefits of restoration, the likelihood of restoration success, the probability of stochastic events, feedbacks, time lags and spatial connectivity.

4. Through collaboration with restoration practitioners we derive quantitative and spatially explicit data on each site requiring restoration. We determine the relative priority for restoring each site and develop a restoration schedule over 20 years.

5. Our results showed that after 20 years a little over a half of the sites requiring restoration are likely be successfully restored, while the total expenditure at our site will be c. US$13·7 million – almost the entire budget of $14 million.

6. Synthesis and applications. Our restoration prioritization approach provides a schedule for where and when restoration should occur, and also provides operational guidance and support for cost-effective restoration planning such as informing the likely total cost of restoration.

Figure 4. A draft schedule for restoration (a) year 1, (b) year 5, (c) year 10, (d) year 15 and (e) year 20 for the maximize marginal return-on-investment heuristic, using the best solution over each timeframe. The probability of restoration being initiated at each site after 20 years is displayed in (f).